WARNING: This article may be obsoleteThis post was published in 2022-07-10. Obviously, expired content is less useful to users if it has already pasted its expiration date.
This article is categorized as "Garbage" . It should NEVER be appeared in your search engine's results.Table of Contents
（失败！）打算补全之前没搞完的三角函数正交性相关的知识
复习：🔗 [2022-06-09 - Truxton's blog] https://truxton2blog.com/2022-06-09/ 的目录1~2.4
哎呀，很不争气，正交性一点都没看，基础知识又补充复习了一大堆。
补充的内容：
Segmented k-means
继续学习「数位语音处理」的NTU公开课
上一次学习的笔记在：🔗 [2022-03-20 - Truxton's blog] https://truxton2blog.com/2022-03-20/
从这里开始继续学习：
segmented k-means: 这是紧接着这个笔记的未完成内容：🔗 [2022-03-20 - Truxton's blog] https://truxton2blog.com/2022-03-20/
Discrete HMM的例子最容易理解，通过理解最后一张图片的例子可以帮助快速理解之前的GMM模型的例子。
为了防止遗忘：
🔗 [2022-03-19 - Truxton's blog] https://truxton2blog.com/2022-03-19/
EM算法需要指定k值
EM算法是需要指定k（cluster）的！
🔗 [mr-easy/GMM-EM-Python: Python implementation of EM algorithm for GMM. And visualization for 2D case.] https://github.com/mr-easy/GMM-EM-Python
直观的gif图：https://raw.githubusercontent.com/mr-easy/GMM-EM-Python/master/combined.gif
input 4：生成3簇GMM混合数据；input 7：GMM模型指定cluster=3
千万不要再搞错了！！！
另：本站之前涉及到EM算法的笔记：🔗 [2021-11-22 - Truxton's blog] https://truxton2blog.com/2021-11-22/
